删除零线2-D numpy数组 [英] remove zero lines 2-D numpy array

问题描述

我在numpy中运行qr factorization，它返回ndarrays的列表，即Q和R:

I run a qr factorization in numpy which returns a list of ndarrays, namely Qand R:

>>> [q,r] = np.linalg.qr(np.array([1,0,0,0,1,1,1,1,1]).reshape(3,3))

R是一个二维数组，在底部具有旋转的零线(即使在我的测试集中为所有示例都证明了这一点):

R is a two-dimensional array, having pivoted zero-lines at the bottom (even proved for all examples in my test set):

>>> print r
[[ 1.41421356  0.70710678  0.70710678]
 [ 0.          1.22474487  1.22474487]
 [ 0.          0.          0.        ]]

.现在，我想将R分为两个矩阵R_~:

. Now, I want to divide R in two matrices R_~:

[[ 1.41421356  0.70710678  0.70710678]
 [ 0.          1.22474487  1.22474487]]

和R_0:

[[ 0.          0.          0.        ]]

(提取所有零线).似乎接近此解决方案:删除numpy数组中的行.

(extracting all zero-lines). It seems to be close to this solution: deleting rows in numpy array.

更有趣的是:np.linalg.qr()返回一个n x n-矩阵.不，我期望的是:

Even more interesting: np.linalg.qr() returns a n x n-matrix. Not, what I would have expected:

A := n x m
Q := n x m
R := n x m

推荐答案

将np.all与axis参数一起使用:

>>> r[np.all(r == 0, axis=1)]
array([[ 0.,  0.,  0.]])
>>> r[~np.all(r == 0, axis=1)]
array([[-1.41421356, -0.70710678, -0.70710678],
       [ 0.        , -1.22474487, -1.22474487]])

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